Citation

Sapumohotti, Chamal (2013) Design of location fingerprinting systems for Wireless Local Area Networks. Masters thesis, Multimedia University.

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Abstract

Wireless Local Area Network location fingerprinting has emerged as a key enabler for Location Based Services (LBS) in indoor environment. Careful design of location fingerprinting systems is necessary in order to ensure that the localization information is able to meet the Quality of Service requirements of the LBS. Furthermore, location fingerprinting systems have a high labour cost associated with the offline calibration phase and system testing, which limits the feasibility of some design approaches. Consequently, there is a need for design tools which takes in to account these limitations. This thesis proposed three such design tools. Firstly, a measurement framework for supporting measurements related to location fingerprinting systems was introduced. This framework referred to as Location Fingerprinting Measurement Framework (LFMF) significantly reduces errors and tedious steps in data acquisition for system designers. Secondly, a simulation testbed referred to as WiLocSim was proposed as a tool for the comparison of localization algorithms and associated design trade-offs. This was built around a beacon RSS simulator which consists of the physical processes models of multipath propagation, measurement noise and body loss. The beacon RSS simulator in WiLocSim was verified on its ability to reasonably approximate the measurement values by comparing with measurement data. Next, WiLocSim was applied for asymptotic performance analysis of nearest neighbour classification algorithms and the results of the simulation agreed with measurement based experiments in literature. Thirdly, LocationInfo which is a metric to quantify the localization efficacy of APs prior to calibration phase was introduced. This metric was able to solve the problems of identifying the optimal AP deployment locations as well as filtering of APs which do not significantly improve the localization accuracy in crowded WLAN environments.

Item Type:	Thesis (Masters)
Additional Information:	Call No.: TK7882.B56 S27 2013
Uncontrolled Keywords:	Biometric identification
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	14 Jan 2016 07:10
Last Modified:	14 Jan 2016 07:10
URII:	http://shdl.mmu.edu.my/id/eprint/6274

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